F1000Research 2021, 10:249 Last updated: 01 SEP 2021 SOFTWARE TOOL ARTICLE MIREyA: a computational approach to detect miRNA- directed gene activation [version 2; peer review: 1 approved, 2 approved with reservations] Anna Elizarova 1,2, Mumin Ozturk3,4, Reto Guler3-5, Yulia A. Medvedeva1,2 1Group of Regulatory Transcriptomics and Epigenomics, Research Center of Biotechnology, Institute of Bioengineering, Russian Academy of Sciences, Moscow, 117312, Russian Federation 2Department of Biological and Medical Physics, Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, 141701, Russian Federation 3International Centre for Genetic Engineering and Biotechnology, Cape Town, Cape Town, 7925, South Africa 4Department of Pathology, University of Cape Town, Institute of Infectious Diseases and Molecular Medicine (IDM), Division of Immunology and South African Medical Research Council (SAMRC) Immunology of Infectious Diseases, Faculty of Health Sciences, Cape Town, 7925, South Africa 5Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa), Institute of Infectious Disease and Molecular Medicine (IDM), Faculty of Health Sciences, University of Cape Town, Cape Town, 7925, South Africa v2 First published: 29 Mar 2021, 10:249 Open Peer Review https://doi.org/10.12688/f1000research.28142.1 Latest published: 26 Aug 2021, 10:249 https://doi.org/10.12688/f1000research.28142.2 Reviewer Status Invited Reviewers Abstract Emerging studies demonstrate the ability of microRNAs (miRNAs) to 1 2 3 activate genes via different mechanisms. Specifically, miRNAs may trigger an enhancer promoting chromatin remodelling in the version 2 enhancer region, thus activating the enhancer and its target genes. (revision) report Here we present MIREyA, a pipeline developed to predict such miRNA- 26 Aug 2021 gene-enhancer trios based on an expression dataset which obviates the need to write custom scripts. We applied our pipeline to primary version 1 murine macrophages infected by Mycobacterium tuberculosis (HN878 29 Mar 2021 report report report strain) and detected Mir22, Mir221, Mir222, Mir155 and Mir1956, which could up-regulate genes related to immune responses. We believe that MIREyA is a useful tool for detecting putative miRNA- 1. Michiel Jan Laurens De Hoon , RIKEN directed gene activation cases. MIREyA is available from: Center for Integrative Medical Sciences, https://github.com/veania/MIREyA Yokohama, Japan Keywords microRNA, miRNA, non-coding RNA, enhancer, regulator, 2. Xiangfu Zhong , Karolinska Institutet, macrophage, tuberculosis Stockholm, Sweden 3. Chaogang Shao, Huzhou University, Huzhou, China Any reports and responses or comments on the article can be found at the end of the article. Page 1 of 21 F1000Research 2021, 10:249 Last updated: 01 SEP 2021 Corresponding authors: Anna Elizarova ([email protected]), Yulia A. Medvedeva ([email protected]) Author roles: Elizarova A: Conceptualization, Investigation, Methodology, Software, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing; Ozturk M: Funding Acquisition, Methodology, Writing – Review & Editing; Guler R: Funding Acquisition, Writing – Review & Editing; Medvedeva YA: Conceptualization, Funding Acquisition, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Competing interests: No competing interests were disclosed. Grant information: This work was partially supported by RFBR 17-54-80033 grant to YAM. This work was supported by EDCTP postdoctoral fellowship to MO, grants from the South Africa National Research Foundation (NRF) / Department of Science and Innovation (DSI)-South African Research Chair Initiative (SARCHi), as well as the NRF / DSI-BRICS Multilateral Joint Science and Technology Research Collaboration grant number 110482 to RG. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2021 Elizarova A et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite this article: Elizarova A, Ozturk M, Guler R and Medvedeva YA. MIREyA: a computational approach to detect miRNA- directed gene activation [version 2; peer review: 1 approved, 2 approved with reservations] F1000Research 2021, 10:249 https://doi.org/10.12688/f1000research.28142.2 First published: 29 Mar 2021, 10:249 https://doi.org/10.12688/f1000research.28142.1 Page 2 of 21 F1000Research 2021, 10:249 Last updated: 01 SEP 2021 REVISED Amendments from Version 1 This version contains several minor changes. First of all, we added a more detailed explanation of arguments which a user provides to our pipeline and description of the output of the pipeline. Secondly, the missing number of enhancers is now present in table 2. Thirdly, we improved logging of the pipeline in the new version and updated an archived version of the repository. We also corrected the percent identity (PI) threshold from 0.5 to 50 to fit the definition of the percent in the text and we made corresponding changes in the code. Other minor changes include a change of a reference 1, a fix in a gene name Dot1l. Any further responses from the reviewers can be found at the end of the article Introduction Conventionally, microRNAs (miRNAs) are considered to suppress gene expression through RNA interference (RNAi) by binding complementarily to mRNAs, forming a RISC complex, and causing RNA degradation.1 However, recent studies provide evidence that some miRNAs act in the opposite way – stimulating gene activation. Numerous studies have demonstrated the ability of miRNAs to up-regulate genes by targeting their promoters.2,3 Ago1 from miRNA-Ago complex associates with the Ccnb1 promoter and miR-744 induces enrichment of RNA Pol II and H3K4me3 at the Ccnb1 transcription start site.3 MiRNA let-7i interacts with the TATA-box of IL-2 gene and stimulates transcription initiation by contributing to the assembly of the pre-initiation complex.4 Relatively fewer miRNAs demonstrated the ability to unconventionally target and activate enhancers, thus inducing genes regulated by these enhancers. MiR-24-1 acts as a modulator of the chromatin state of an enhancer. Furthermore, it increases p300 and RNA Pol II binding at the enhancer locus. The miR-24-1 actually originates from the enhancer locus. However, some genes regulated by other enhancers are also expressed at higher levels when miR-24-1 is transfected, and the enhancers of induced genes contain a sequence similar to the seed of the miRNA.5 These observations suggest that other miRNAs might trigger enhancers and activate gene expression. When miRNAs function as activators in a nucleus, different targeting mechanisms are possible: miRNA:DNA Watson- Crick duplex formation as well as miRNA:DNA Hoogsteen triple helix formation. Nuclear miRNA target prediction tools utilize are based on the idea that miRNA:DNA interaction requires an intact seed region.6 MicroPIR2 predicts targets in mouse and human promoter regions.7 Trident predicts miRNA:DNA Hoogsteen-type base pairings.8 Some tools designed to predict conventional miRNA targets may also be utilized to find nuclear activational targets, e.g. miRanda.9 In this work, we report MIREyA (MIRnas functioning through Enhancer Activation), a pipeline for detection of miRNAs and their gene targets up-regulated through triggering their enhancer in the provided expression dataset. We applied MIREyA in order to identify and characterize activational miRNAs in Mycobacterium tuberculosis (Mtb) infected macrophage dataset. MiRNAs are important regulators in macrophage responses during Mtb infection that may act as host immunity agents as well as a tool exploited by pathogen agents to manipulate host cell pathways.10 Yet, only the – classical role of miRNA has been investigated so far in the context of Mtb infection.11 19 Although multiple studies have shown the possibility of the activational role of miRNAs, this potential remains neglected in the study of miRNAs in bacterial infections. MIREyA found several miRNAs, which have not been shown to be functional in TB yet, suggesting it could be useful to find candidate activational miRNAs for further experimental validation. Mir155 has previously been shown to act as a negative regulator of essential mRNAs during TB,20,21 but not as an activator. Methods Main steps of the algorithm MIREyA aims to detect miRNAs with the potential to upregulate a gene via activation of its enhancer. It consists of three major steps: 1) The algorithm detects miRNA bound to the enhancers. This step is implemented with three different approaches described below. 2) The algorithm selects genes regulated by the enhancers selected in step 1). For this step the output from the first step is required as well as a table with enhancer:gene pairs where an enhancer is assumed to regulate the corresponding gene. 3) The algorithm calculates the Spearman’s correlation coefficient (SCC) between the expression levels of miRNAs and genes regulated by corresponding enhancers selected in step 1), and estimates the p-value of the SCC with a Benjamini-Hochberg correction using the number of the miRNA:gene pairs for one miRNA (FDR < 0.05). The input data is gene expression data with sample size ≥ 8 and the output of the previous step. Page 3 of 21 F1000Research 2021, 10:249 Last updated: 01 SEP